COVID-19’DA KARDİYOTORASİK RADYOLOJİK GÖRÜNTÜLEME VE YAPAY ZEKANIN ROLÜ

Year 2021, , 101 - 112, 01.05.2021

Veysel Atilla Ayyıldız

https://doi.org/10.17343/sdutfd.902875

Abstract

ÖZET
Covid-19'un görüntülemesiyle ilgili bulgular 2020'nin başlarında yayınlandığından beri çok şey öğrenildi. Görüntüleme çalışmalarını bildirmek için birçok sınıflandırma sistemi, karakteristik görüntüleme bulgularına dayanarak geliştirilmiştir. Görüntülemedeki artmış performans ve RT-PCR (Revers Transkriptaz-Polimeraz Zincir Reaksiyonu) testine erişimin kolaylaşması sonucu görüntüleme yalnızca daha şiddetli hastalığı olan veya solunumu kötüleşen hastalar için endikedir. Enfeksiyon, asemptomatik tablodan şiddetli ve bazen ölümcül hastalığa kadar değişen bir spektrumda ortaya çıkmakla beraber, en sık akut akciğer hasarı görülür. Görüntüleme başlangıçta alternatif olarak BT (Bilgisayarlı Tomografi) ile ortaya çıkıp sonradan muhtemelen RT-PCR'na kıyasla daha üstün bir test olarak, spesifik endikasyonlara dayalı daha sınırlı bir rol almıştır. Salgının başlarında, Covid-19 şüphesi olan hastalar için, RT-PCR testinin kullanılabilirliğinin sınırlı olduğu ve performansının belirsiz olduğu durumlarda triyaj amacıyla göğüs görüntüleme için çeşitli sınıflandırma ve raporlama şemaları geliştirilmiştir. Covid-19'a özgü tipik bulgulara sahip özellikler ve alternatif bir tanıyı öneren özellikler için gözlemciler arası anlaşma, çok sayıda çalışmada yüksektir. Göğüs grafisi (GG) ve BT'deki akciğer tutulumunun derecesini değerlendiren bazı çalışmalar, kritik hastalık ve mekanik ventilasyon ihtiyacı ile korelasyon göstermiştir.
Pulmoner belirtilere ek olarak, tromboembolizm ve miyokardit gibi kardiyovasküler komplikasyonlar, bazen nörolojik ve abdominal belirtilere katkıda bulunan Covid-19'a atfedilmiştir. Son olarak yapay zeka, hem radyografi hem de BT açısından Covid-19 pnömonisinin hem tanı hem de prognozunda umut vadetmektedir.

Keywords

Covid 19, Yapay zeka, Bilgisayarlı tomografi, Göğüs grafisi, RT-PCR

Supporting Institution

yok

Project Number

yok

CARDIOTORACIC RADIOLOGICAL IMAGING AND THE ROLE OF ARTIFICIAL INTELLIGENCE IN COVID-19

Abstract

ABSTRACT
Much has been learned since the findings of Covid-19's imaging were published in early 2020. Many classification systems have been developed based on characteristic imaging findings to report imaging studies. As a result of increased performance in imaging and improved access to RT-PCR (Reverse Transcriptase-Polymerase Chain Reaction) testing, imaging is only indicated for patients with more severe disease or worsening breathing. Although the infection occurs in a spectrum ranging from asymptomatic to severe and sometimes fatal disease, acute lung injury is the most common. Imaging initially emerged with CT (Computed Tomography) as an alternative and subsequently played a more limited role based on specific indications, possibly as a superior test compared to RT-PCR. Various classification and reporting schemes have been developed for triage in cases where RT-PCR availability is limited and its performance is uncertain. Interobserver agreement for features with typical findings unique to Covid-19 and features that suggest an alternative diagnosis is high in a large number of studies. Some studies evaluating the degree of lung involvement on chest X-ray and CT have correlated with critical illness and the need for mechanical ventilation.
In addition to pulmonary manifestations, cardiovascular complications such as thromboembolism and myocarditis have sometimes been attributed to Covid-19, which contributes to neurological and abdominal manifestations. Finally, artificial intelligence shows promise in both the diagnosis and prognosis of Covid-19 pneumonia in terms of both radiography and CT.

Keywords

Covid 19, Artificial intelligence, Computed tomography, Chest radiography, RT-PCR

Project Number

yok

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